Wearable device having high security and stable blood pressure detection

ABSTRACT

A wearable device including a skin sensor and a processor is provided. The processor is configured to receive an authentication data for authenticating a user when a wearing state of the wearable device is adjacent to a skin surface of the user, execute a predetermined function in response to a request when the authentication data matches a pre-stored data and the skin sensor determines that the wearable device does not leave the skin surface after the authentication data is received, and reject or ignore the request when the skin sensor determines that the wearable device leaves the skin surface before the predetermined function is executed. The processor further calculates blood pressures according to PPG signals detected by a PPG sensor of the skin sensor.

RELATED APPLICATIONS

The present application is a continuation application of U.S. patentapplication Ser. No. 17/021,336 filed on, Sep. 15, 2020, which acontinuation-in-part application of U.S. patent application Ser. No.16/850,753 filed on, Apr. 16, 2020, which is a continuation applicationof U.S. patent application Ser. No. 16/563,931 filed on, Sep. 9, 2019,which is a continuation-in-part application of U.S. patent applicationSer. No. 16/519,197 filed on, Jul. 23, 2019, which is acontinuation-in-part application of U.S. patent application Ser. No.16/360,605 filed on, Mar. 21, 2019, which is a continuation-in-partapplication of U.S. patent application Ser. No. 16/117,334 filed on,Aug. 30, 2018, which is a continuation-in-part application of U.S.patent application Ser. No. 15/964,718 filed on, Apr. 27, 2018, which isa continuation-in-part application of U.S. patent application Ser. No.15/722,435 filed on, Oct. 2, 2017, which is a continuation-in-partapplication of U.S. patent application Ser. No. 15/343,509 filed on,Nov. 4, 2016, which is a continuation-in-part application of U.S. patentapplication Ser. No. 14/684,648 filed on, Apr. 13, 2015, and claimspriority to Taiwanese Application Number 103123544, filed Jul. 8, 2014,the disclosures of which are hereby incorporated by reference herein intheir entirety. The present application is a continuation application ofU.S. patent application Ser. No. 17/021,336 filed on, Sep. 15, 2020,which is also a continuation-in-part application of U.S. patentapplication Ser. No. 15/350,619 filed on, Nov. 14, 2016, and claimspriority to Taiwanese Application Number 105100804, filed Jan. 12, 2016,the disclosures of which are hereby incorporated by reference herein intheir entirety.

BACKGROUND 1. Field of the Disclosure

This disclosure generally relates to a wearable device and, moreparticularly, to a wearable device and a controlling method thereofcapable of detecting a contact status with a skin surface.

2. Description of the Related Art

Wearable devices, such as smart watches, are getting more and morepopular. Wearable devices can provide various convenient functions, suchas schedule management, emails, heartbeat measurement, and mobilepayment. Some functions require authentication before execution becausethe wearable device must ensure the current user is the owner of thewearable device in order to protect the privacy or the interest of theowner.

However, authentication before execution is not secure enough in somescenarios. For example, an owner of a wearable device passes theauthentication, and then the owner controls the wearable device toexecute an important function such as schedule management, and thensomething unusual distracts the owner from the function, and then theowner puts down the wearable device and walks away. In this case, sincethe wearable device is still in the authenticated state, another usercan pick up the wearable device and look at the owner's privateschedule, even temper with the owner's private schedule.

SUMMARY

The present disclosure is related to a wearable device and a skin sensorthat can make some important functions more secure after userauthentication.

The present disclosure provides a wearable device including a PPG sensorand a processor. The PPG sensor is configured to generate a PPG signal.The processor is configured to receive an authentication data forauthenticating the user when the wearable device is determined to be incontact with a skin surface of the user according to the PPG signal,execute a predetermined function for the user in response to a requestwhen the authentication data matches a pre-stored data and the wearabledevice is determined to be still in contact with the skin surfaceaccording to the PPG signal, and reject or ignore the request when thewearable device is determined to be no longer in contact with the skinsurface according to the PPG signal after the authentication data isreceived and before the predetermined function is executed. Theprocessor is further configured to calculate at least one blood pressurecorresponding to each pulse duration according to at least one bloodpressure estimation model and a time difference between two featurepoints within one pulse duration of the PPG signal, and averagecalculated blood pressures within a predetermined time interval togenerate an average blood pressure.

The present disclosure further provides a wearable device including aPPG sensor and a processor. The PPG sensor is configured to generate aPPG signal. The processor is configured to enter a first mode or asecond mode. In the first mode, the processor is configured to receivean authentication data for authenticating the user when the wearabledevice is determined to be in contact with a skin surface of the useraccording to the PPG signal, execute a predetermined function for theuser in response to a request when the authentication data matches apre-stored data and the wearable device is determined to be still incontact with the skin surface according to the PPG signal, and reject orignore the request when the wearable device is determined to be nolonger in contact with the skin surface according to the PPG signalafter the authentication data is received and before the predeterminedfunction is executed. In the second mode, the processor is configured tocalculate at least one blood pressure corresponding to each pulseduration according to at least one blood pressure estimation model and atime difference between two feature points within one pulse duration ofthe PPG signal, and average calculated blood pressures within apredetermined time interval to generate an average blood pressure.

The present disclosure further provides a wearable device including aPPG sensor and a processor. The PPG sensor is configured to generate aPPG signal according to samples acquired at a sampling frequency of thePPG sensor. The processor is configured to receive an authenticationdata for authenticating the user when the wearable device is determinedto be in contact with a skin surface of the user according to an oddnumber of the samples of the PPG signal, execute a predeterminedfunction for the user in response to a request when the authenticationdata matches a pre-stored data and the wearable device is determined tobe still in contact with the skin surface according to the odd number ofthe samples of the PPG signal, and reject or ignore the request when thewearable device is determined to be no longer in contact with the skinsurface according to the odd number of the samples of the PPG signalafter the authentication data is received and before the predeterminedfunction is executed. The processor is further configured to calculateat least one blood pressure corresponding to each pulse durationaccording to at least one blood pressure estimation model and a timedifference between two feature points within one pulse duration of thePPG signal using an even number of the samples of the PPG signal, andaverage calculated blood pressures within a predetermined time intervalto generate an average blood pressure.

BRIEF DESCRIPTION OF THE DRAWINGS

Other objects, advantages, and novel features of the present disclosurewill become more apparent from the following detailed description whentaken in conjunction with the accompanying drawings.

FIG. 1 is a block diagram showing a wearable device according to anembodiment of the present disclosure.

FIG. 2 is a block diagram showing a skin sensor of a wearable deviceaccording to an embodiment of the present disclosure.

FIG. 3 is a flow chart showing a method for controlling a wearabledevice according to an embodiment of the present disclosure.

FIG. 4 is a schematic diagram of a photoplethysmography (PPG) signaldetected by a wearable device according to one embodiment of the presentdisclosure.

FIG. 5 is a schematic diagram of blood pressures obtained by a bloodpressure estimation model according to one embodiment of the presentdisclosure.

FIGS. 6A and 6B are usage states of a wearable device according to someembodiments of the present disclosure.

FIG. 7 is a schematic block diagram of a wearable device according toone embodiment of the present disclosure.

FIG. 8 is a schematic diagram of average blood pressures according toone embodiment of the present disclosure.

FIG. 9 is a flow chart of an operating method of a wearable deviceaccording to one embodiment of the present disclosure.

DETAILED DESCRIPTION OF THE EMBODIMENT

It should be noted that, wherever possible, the same reference numberswill be used throughout the drawings to refer to the same or like parts.The separate embodiments in the present disclosure below may be combinedtogether to achieve superimposed functions.

FIG. 1 is a block diagram showing a wearable device 100 according to anembodiment of the present disclosure. For example, the wearable device100 is a smart watch, a smart wristband, a smart earphone, a smart shoe,or a pair of smart glasses. The wearable device 100 includes a skinsensor 110, a processor 130, an input device 140, an output device 150,and a wireless communication device 160. The processor 130 iselectrically coupled to the skin sensor 110, the input device 140, theoutput device 150, and the wireless communication device 160. In onenon-limiting aspect, the skin sensor 110 and the processor 130 areencapsulated in the same sensor chip.

The skin sensor 110 is equipped on a side (e.g., back side) of thewearable device 100 close to a skin surface of a user when the wearabledevice 100 is worn on the user. The skin sensor 110 is configured todetect the skin surface and further in some cases to detect whether thewearable device 100 leaves the skin surface of the user. The inputdevice 140 is configured to receive user input for the wearable device100. The output device 150 is configured to output data and/orinformation to the user and is also configured to display graphical userinterfaces of the operating system and the applications of the wearabledevice 100. The wireless communication device 160 is configured totransmit and receive data and signals between the wearable device 100and external electronic devices through wireless communication. Thewireless communication device 160 uses low power wireless technology,such as Near Field Communication (NFC) technology, Bluetooth technology,Wi-Fi technology, wireless local area network (WLAN) technology, orcellular network technology for transmitting and receiving data andsignals. The processor 130 is the main processor, the microcontrollerunit (MCU), the central processing unit (CPU) or an application specificintegrated circuit (ASIC) of the wearable device 100. The processor 130is configured to control or cooperate with the skin sensor 110, theinput device 140, the output device 150, and the wireless communicationdevice 160 to execute various functions and applications of the wearabledevice 100.

FIG. 2 is a block diagram showing the skin sensor 110 of the wearabledevice 100 according to an embodiment of the present disclosure. Theskin sensor 110 includes five sub-sensors of different types, forexample, a capacitive sensor 210, an inductive sensor 220, an opticalsensor 230, a photoplethysmography (PPG) sensor 240, and a temperaturesensor 250. The present disclosure is not confined to exactly fivesub-sensors. The number and types of sub-sensors used in the skin sensor110 may be adjusted in another embodiment. Each sub-sensor of the skinsensor 110 is configured to use a different sensing method to detect theskin surface of a user and provide a detecting result indicating theresult of detecting the skin surface. The skin sensor 110 furtherincludes a register 260. More details of the skin sensor 110 arediscussed below with reference to FIG. 3 .

FIG. 3 is a flow chart showing a method for controlling a wearabledevice according to an embodiment of the present disclosure. Thewearable device 100 executes the method in FIG. 3 starting from step302.

At step 302, the skin sensor 110 determines a wearing state of thewearable device 100 according to (e.g., collecting and comparing) atleast one of the detecting results of the sub-sensors of the skin sensor110. The wearing state of the wearable device 100 is either “adjacent orattached to the skin surface of the user” or “not adjacent or attachedto the skin surface of the user”. The correspondence between the wearingstate and the detecting result of each sub-sensor is described below.

The capacitive sensor 210 includes at least one electrode 213. The atleast one electrode 213 is selected to be positioned on an externalsurface of the housing of the wearable device 100. Alternatively, the atleast one electrode 213 is selected to be exposed outside the externalsurface of the housing of the wearable device 100. Alternatively, the atleast one electrode 213 is selected to be embedded in the housing of thewearable device 100 or positioned in an internal space enclosed by thehousing of the wearable device 100. The capacitive sensor 210 measuresthe capacitance value of the at least one electrode 213 and outputs acorresponding capacitance value as the detecting result of thecapacitive sensor 210. The capacitance value output by the capacitivesensor 210 is the capacitance value of the at least one electrode 213,or a voltage value or a length of charging/discharging time indicatingthe capacitance value of the at least one electrode 213. Since the skinof the user is an electrical conductor, approaching or leaving the skinsurface of the user results in a distortion of the electrostatic fieldgenerated by the at least one electrode 213, and the capacitance valueof the at least one electrode 213 changes according to the distortion ofthe electrostatic field. Therefore, the skin sensor 110 can determinethe wearing state of the wearable device 100 according to thecapacitance value output by the capacitive sensor 210.

In an embodiment, the capacitance value output by the capacitive sensor210 increases when the wearable device 100 approaches the skin surfaceof the user and the capacitance value output by the capacitive sensor210 decreases when the wearable device 100 leaves the skin surface ofthe user. The capacitance value output by the capacitive sensor 210indicates that the wearing state of the wearable device 100 is adjacentto the skin surface of the user when the capacitance value is higherthan or increases more than a threshold value, while the capacitancevalue output by the capacitive sensor 210 indicates that the wearingstate of the wearable device 100 is not adjacent to the skin surface ofthe user when the capacitance value is lower than or decreases more thanthe threshold value.

In another embodiment, the capacitance value output by the capacitivesensor 210 decreases when the wearable device 100 approaches the skinsurface of the user and the capacitance value output by the capacitivesensor 210 increases when the wearable device 100 leaves the skinsurface of the user. The capacitance value output by the capacitivesensor 210 indicates that the wearing state of the wearable device 100is adjacent to the skin surface of the user when the capacitance valueis lower than or decreases more than a threshold value, while thecapacitance value output by the capacitive sensor 210 indicates that thewearing state of the wearable device 100 is not adjacent to the skinsurface of the user when the capacitance value is higher than orincreases more than the threshold value.

The threshold value can be a constant value or a variable value adaptedto real-time detection. For example, the threshold value can becalculated by adding a predetermined value to or subtracting apredetermined value from a previous capacitance value output by thecapacitive sensor 210.

The inductive sensor 220 includes a transmitter (TX) coil 223 and areceiver (RX) coil 225. The inductive sensor 220 is configured toprovide a current to the transmitter coil 223. When the inductive sensor220 is energized, an electromagnetic field is formed between the TX coil223 and the RX coil 225. A metal object moving relative to the inductivesensor 220 disrupts the electromagnetic field and changes an inducedcurrent on the RX coil 225. The inductive sensor 220 is configured todetect and output a magnitude variation of the induced current in the RXcoil 225 as the detecting result of the inductive sensor 220. When themagnitude variation exceeds (becomes higher or lower than) a thresholdvalue, then a metal object is identified as leaving or approaching thewearable device 100. The metal object affects detecting results of boththe capacitive sensor 210 and the inductive sensor 220.

The inductive sensor 220 can detect a metal object but cannot detect theskin surface of the user. However, since a metal object is also anelectrical conductor, the inductive sensor 220 can cooperate with thecapacitive sensor 210 to differentiate between a metal object and theskin surface of the user so that the detection of the skin sensor 110 isnot misled by the metal object. For example, when the detecting resultsof both the capacitive sensor 210 and the inductive sensor 220 indicatethat an electrical conductor is adjacent to the wearable device 100, theskin sensor 110 is able to know that the wearable device 100 is adjacentto a metal object instead of the skin surface of the user, and thereforethe skin sensor 110 can determine that the wearing state of the wearabledevice 100 is not adjacent to the skin surface of the user.

The optical sensor 230 includes a light source 233 and a light sensor235. The light source 233 is configured to emit light of a singledominant wavelength or a plurality of different dominant wavelengths.For example, in an embodiment, the light source 233 emits visible lightand infrared light. The light sensor 235 is configured to detect theintensity of the light emitted by the light source 233 and thenreflected by or penetrated through an external object, such as the skinsurface of the user. The aforementioned detecting result output by theoptical sensor 230 is the light intensity detected by the light sensor235.

In an embodiment, the light intensity of the light source 233 is higherthan the light intensity of the ambient environment. Therefore, thelight intensity output by the optical sensor 230 increases when thewearable device 100 approaches the skin surface of the user and thelight intensity output by the optical sensor 230 decreases when thewearable device 100 leaves the skin surface of the user.

In another embodiment, the light intensity of the light source 233 islower than the light intensity of the ambient environment, or theoptical sensor 230 does not include the light source 233. Therefore, thelight intensity output by the optical sensor 230 decreases when thewearable device 100 approaches the skin surface of the user and thelight intensity output by the optical sensor 230 increases when thewearable device 100 leaves the skin surface of the user.

The skin sensor 110 can determine the wearing state of the wearabledevice 100 by comparing the light intensity or a variation thereofoutput by the optical sensor 230 with a threshold value. The comparingand the threshold value are similar to those of the capacitive sensor210.

The PPG sensor 240 includes a light source 243 and a light sensor 245.The light source 243 is configured to emit light of a single dominantwavelength or a plurality of different dominant wavelengths toilluminate the skin of the user. For example, in an embodiment, thelight source 243 emits visible light and infrared light. The lightsensor 245 is configured to measure the absorption of the light by theskin of the user to detect blood volume changes in capillaries in theskin of the user caused by the blood pulse of each cardiac cycle of theuser. Based on the blood volume changes, the PPG sensor 240 isconfigured to detect a PPG signal including information representing atleast one of the heart rate, heartbeats, and cardiac cycles of the user.The aforementioned detecting result output by the PPG sensor 240 is thePPG signal.

In an embodiment, the PPG signal indicates that the wearing state of thewearable device 100 is adjacent to the skin surface of the user when thePPG signal includes the heartbeat waveform of at least one completecardiac cycle of the user, while the PPG signal indicates that thewearing state of the wearable device 100 is not adjacent to the skinsurface of the user when the PPG signal does not include any heartbeatwaveform of the user. This is a slower method for determining thewearing state of the wearable device 100 because the PPG sensor 240needs approximately one second to output the heartbeat waveform of onecomplete cardiac cycle.

It is also possible to determine the wearing state of the wearabledevice 100 by calculating a signal-to-noise ratio or comparingamplitudes of the PPG signal with a threshold value. In an exemplaryembodiment, the PPG signal indicates that the wearing state of thewearable device 100 is adjacent to the skin surface of the user when asignal-to-noise ratio or an amplitude of the PPG signal is higher thanor becomes higher than a threshold value, while the PPG signal indicatesthat the wearing state of the wearable device 100 is not adjacent to theskin surface of the user when the signal-to-noise ratio or the amplitudeof the PPG signal is lower than or becomes lower than the thresholdvalue. This is also a slower method for determining the wearing state ofthe wearable device 100 because the signal-to-noise ratio and theamplitude need the heartbeat waveform of at least one complete cardiaccycle to calculate.

It is also possible to determine the wearing state of the wearabledevice 100 by comparing signal values or magnitudes of the PPG signalwith a threshold value. In an exemplary embodiment, the PPG signalindicates that the wearing state of the wearable device 100 is adjacentto the skin surface of the user when a signal value or a magnitude ofthe PPG signal is higher than or becomes higher than a threshold value,while the PPG signal indicates that the wearing state of the wearabledevice 100 is not adjacent to the skin surface of the user when thesignal value or the magnitude of the PPG signal is lower than or becomeslower than the threshold value. This is a much faster method fordetermining the wearing state of the wearable device 100 because theskin sensor 110 only needs to obtain an instant signal value or aninstant magnitude of the PPG signal to determine the wearing state.

In one non-limiting embodiment, the optical sensor 230 is replaced bythe PPG sensor 240. That is, the wearable device 100 does not includethe optical sensor 230, and the PPG sensor 240 detects and outputs boththe light intensity and the PPG signal mentioned above as the detectingresult.

In an embodiment, the output device 150 includes a display configured todisplay the information of the PPG signal so that the user can view atleast one of his/her heart rate, heartbeats and cardiac cycles as wellas whether the wearable device 100 is adjacent to or leaving from theskin surface of the user indicated by each of the sub-sensors. Inaddition, the wireless communication device 160 is configured totransmit the PPG signal to an external electronic device for display,analysis, processing, or storage.

The temperature sensor 250 includes a thermocouple or a resistancetemperature detector configured to detect and output a temperature valuecorresponding to the temperature of the skin surface of the user as thedetecting result of the temperature sensor 250. The temperature valueindicates that the wearing state of the wearable device 100 is adjacentto the skin surface when the difference value between the temperaturevalue and a pre-stored skin temperature is smaller than or becomessmaller than a threshold value, while the temperature value indicatesthat the wearing state of the wearable device 100 is not adjacent to theskin surface when the difference value between the temperature value andthe pre-stored skin temperature is larger than or becomes larger thanthe threshold value. In another aspect, when a detected temperaturevalue is larger than a predetermined threshold value, it means that thewearable device 100 is in an adjacent state (adjacent to the skinsurface of the user); otherwise, the wearable device 100 is in anon-adjacent state (not adjacent to the skin surface of the user).

In an embodiment, the skin sensor 110 includes only one sub-sensor, orthe skin sensor 110 is replaced by the only one sub-sensor. For example,the only one sub-sensor is the capacitive sensor 210, the optical sensor230, the PPG sensor 240, or the temperature sensor 250. The skin sensor110 is configured to determine the wearing state of the wearable device100 according to the detecting result output by the only one sub-sensor.

In another embodiment, the skin sensor 110 includes a plurality ofsub-sensors. For example, each sub-sensor is the capacitive sensor 210,the inductive sensor 220, the optical sensor 230, the PPG sensor 240, orthe temperature sensor 250. The skin sensor 110 is configured todetermine that the wearing state of the wearable device 100 is adjacentto the skin surface of the user when all of the detecting results of thesub-sensors indicate that the wearing state of the wearable device 100is adjacent to the skin surface. The skin sensor 110 is furtherconfigured to determine that the wearing state of the wearable device100 is not adjacent to the skin surface when at least one or apredetermined number of the detecting results of the sub-sensorsindicates that the wearing state of the wearable device 100 is notadjacent to the skin surface.

Each single sub-sensor can be affected by interferences in the ambientenvironment. For example, the capacitive sensor 210 and the inductivesensor 220 can be affected by electrical conductors nearby. The opticalsensor 230 and the PPG sensor 240 can be affected by external lightsources and ambient brightness. The temperature sensor 250 can beaffected by ambient temperatures. Multiple sub-sensors in the skinsensor 110 can make the detection of the skin sensor 110 more reliableby covering each other's weakness.

In another embodiment, the skin sensor 110 does not determine thewearing state of the wearable device 100. Instead, the skin sensor 110transmits the detecting results of the sub-sensors to the processor 130,and the processor 130 determines the wearing state of the wearabledevice 100 according to the detecting results in the same way as theskin sensor 110 determines the wearing state in the previousembodiments.

In one non-limiting embodiment, the PPG sensor 240 is not included inthe skin sensor 110. Instead, the PPG sensor 240 is a part of thewearable device 100 outside the skin sensor 110. The detection rate ofthe skin sensor 110 is faster than the detection rate of the PPG sensor240. The skin sensor 110 does not determine the wearing state of thewearable device 100. Instead, the PPG sensor 240 determines the wearingstate of the wearable device 100 according to the PPG signal. Morespecifically, the PPG sensor 240 determines whether the wearable device100 is worn on the user (step 302) with a slower (compared with the skinsensor 110) detecting rate; whereas, the skin sensor 110 determineswhether the wearable device 100 leaves (step 308) from the skin surface,after the adjacent state is confirmed, with a higher (compared with thePPG sensor 240) detecting rate.

In another embodiment, the PPG sensor 240 is a part of the wearabledevice 100 outside the skin sensor 110. The wearing state of thewearable device 100 is not determined by the skin sensor 110 or the PPGsensor 240. Instead, the PPG sensor 240 transmits the PPG signal to theprocessor 130, and the processor 130 determines the wearing state of thewearable device 100 according to the PPG signal in the same way as thePPG sensor 240 determines the wearing state in the previous embodiment.

The flow in FIG. 3 returns to repeat step 302 when the skin sensor 110,the PPG sensor 240 or the processor 130 determines that the wearingstate of the wearable device 100 is not adjacent to the skin surface ofthe user. The flow proceeds to step 304 when the skin sensor 110, thePPG sensor 240 or the processor 130 determines that the wearing state ofthe wearable device 100 is adjacent to the skin surface of the user.

Next, at step 304, the processor 130 controls the input device 140 ofthe wearable device 100 to receive an authentication data generated byoperations and/or physiological characteristics of the user. Theauthentication data is for user authentication before executing thepredetermined function of the wearable device 100. The predeterminedfunction is an important function exclusive to the owner of the wearabledevice 100. Therefore, user authentication is necessary to ensure thatthe current user is the owner of the wearable device 100. For example,the predetermined function is mobile payment, accessing restricted data,or performing restricted electronic transmission with an externalelectronic device.

For example, the input device 140 includes a keypad, a keyboard, or atouch panel for the user to input a password and the authentication dataincludes the password.

For example, the input device 140 includes a touch panel. The user canmove a finger or a stylus on the touch panel to input a sliding track.The authentication data includes the sliding track.

For example, the input device 140 includes a camera. The user canperform at least one gesture with a part of his/her body (such as a palmor a hand) or his/her entire body. The camera is configured to take atleast one image of the at least one gesture. The authentication dataincludes the at least one image of the at least one gesture.Alternatively, the input device 140 can extract image features from theat least one image of the at least one gesture and the authenticationdata includes the image features.

For example, the input device 140 includes a biometric sensor or acamera for obtaining a biometric data of the user based on physiologicalcharacteristics of the user, such as voiceprint, fingerprint, palmprint, palm veins pattern, hand geometry, iris pattern, retina pattern,and/or facial geometry. The authentication data includes the biometricdata.

For example, the input device 140 includes at least one of theaforementioned keypad, keyboard, touch panel, camera, and biometricsensor, and the authentication data includes at least one of theaforementioned password, sliding track, image of gesture, image featuresof image of gesture, and biometric data.

Next, at step 306, the processor 130 performs the aforementioned userauthentication by determining whether the authentication data matcheswith a pre-stored data. The pre-stored data is associated with theidentity of the owner of the wearable device 100. For example, thepre-stored data is a password or a digital signature set by the owner ora biometric data based on physiological characteristics of the owner.When the authentication data does not match with the pre-stored data,the user authentication fails and the flow returns to step 302. When theauthentication data matches with the pre-stored data, the user passesthe authentication successfully and the flow proceeds to step 308.

In an embodiment, the pre-stored data is stored in the wearable device100. The processor 130 compares the authentication data with thepre-stored data and determines whether the authentication data matcheswith the pre-stored data according to the result of the comparison.

In another embodiment, the pre-stored data is stored in an externalelectronic device. The processor 130 obtains the pre-stored data fromthe external electronic device through the wireless communication device160, compares the authentication data with the pre-stored data, anddetermines whether the authentication data matches with the pre-storeddata according to the result of the comparison.

In another embodiment, the pre-stored data is stored in an externalelectronic device. The processor 130 transmits the authentication datato the external electronic device through the wireless communicationdevice 160. The external electronic device compares the authenticationdata with the pre-stored data and transmits the result of the comparisonto the wearable device 100. The processor 130 determines whether theauthentication data matches with the pre-stored data according to theresult of the comparison.

At step 308, the skin sensor 110 determines whether the wearable device100 leaves the skin surface of the user regularly or before thepredetermined function is executed. The skin sensor 110 can determine acurrent wearing state of the wearable device 100 according to thecurrent detecting result output by at least one of the sub-sensors ofthe skin sensor 110. When the current detecting result includes the PPGsignal output by the PPG sensor 240, the skin sensor 110 determines thecurrent wearing state according to the signal value or the magnitude ofthe PPG signal instead of complete cardiac cycles in the PPG signalbecause the leaving of the wearable device 100 from the skin surfacemust be detected as soon as possible for security reasons (more detailslater). When the skin sensor 110 determines that the current wearingstate is still adjacent to the skin surface (since step 302), that meansthe wearable device 100 does not leave the skin surface. When the skinsensor 110 determines that the current wearing state is no longeradjacent to the skin surface, that means the wearing state changes fromadjacent to the skin surface (at step 302) to not adjacent to the skinsurface (at step 308). In response, the skin sensor 110 determines thatthe wearable device 100 leaves the skin surface.

In another embodiment, when the detecting result output by a sub-sensorof the skin sensor 110 indicates that the wearing state of the wearabledevice 100 is still adjacent to the skin surface (since step 302), thedetecting result of that sub-sensor indicates that the wearable device100 does not leave the skin surface. When the detecting result output bya sub-sensor of the skin sensor 110 indicates that the wearing state ofthe wearable device 100 is no longer adjacent to the skin surface, thedetecting result of that sub-sensor indicates that the wearable device100 leaves the skin surface. The skin sensor 110 is configured todetermine that the wearable device 100 does not leave the skin surfacewhen all of the detecting results of the sub-sensors indicate that thewearable device 100 does not leave the skin surface. The skin sensor 110is further configured to determine that the wearable device 100 leavesthe skin surface when at least one of the detecting results of thesub-sensors indicates that the wearable device 100 leaves the skinsurface or when at least two of the detecting results of the sub-sensorscannot indicate whether or not the wearable device 100 leaves the skinsurface.

In a non-limiting embodiment, the sub-sensors in the skin sensor 110 canbe classified into a main sub-sensor and one or more auxiliarysub-sensors. The skin sensor 110 can determine whether the wearabledevice 100 leaves the skin surface according to the detecting resultsoutput by the main sub-sensor and at least one auxiliary sub-sensor. Theskin sensor 110 checks the detecting result of the main sub-sensor firstand then check the detecting results of the auxiliary sub-sensors. Forexample, the capacitive sensor 210 is the main sub-sensor and the othersub-sensors are the auxiliary sub-sensors. The skin sensor 110 can checkthe detecting results of all of the sub-sensors one by one according toa preset order.

When the skin sensor 110 determines that the wearable device 100 leavesthe skin surface, the skin sensor 110 sets a notification to notify theprocessor 130 that the wearable device 100 leaves the skin surface. Inan embodiment, the skin sensor 110 includes a register 260 readable bythe processor 130. The skin sensor 110 sets the notification by changingthe value stored in the register 260 from a first value to a secondvalue. The processor 130 can keep reading the value stored in theregister 260 to know whether the wearable device 100 leaves the skinsurface of the user. When the value read from the register 260 is thefirst value, that means the wearable device 100 does not leave the skinsurface of the user. When the value read from the register 260 is thesecond value, that means the wearable device 100 leaves the skin surfaceof the user.

When the wearable device 100 leaves the skin surface and then approachesthe skin surface between steps 302 and 308, the skin sensor 110 does notchange the value stored in the register 260 back to the first value.Instead, the skin sensor 110 keeps the second value in the register 260to ignore the approaching of the wearable device 100 to the skin surfaceafter the leaving from the skin surface so that the wearable device 100will be determined to leave the skin surface at step 308.

In another embodiment, the register 260 is not implemented. The skinsensor 110 sets the notification by transmitting a notification signalto the processor 130. The processor 130 can know whether the wearabledevice 100 leaves the skin surface of the user by checking thenotification signal. When the processor 130 does not receive thenotification signal, that means the wearable device 100 does not leavethe skin surface of the user. When the processor 130 receives thenotification signal, that means the wearable device 100 leaves the skinsurface of the user.

When the wearable device 100 leaves the skin surface and then approachesthe skin surface between steps 302 and 308, the skin sensor 110 does notwithdraw the notification signal, thus the skin sensor 110 ignores theapproaching of the wearable device 100 to the skin surface after theleaving from the skin surface so that the wearable device 100 will bedetermined to leave the skin surface at step 308.

In another embodiment, the skin sensor 110 does not determine whetherthe wearable device 100 leaves the skin surface. Instead, the skinsensor 110 transmits the detecting results of the sub-sensors to theprocessor 130, and the processor 130 determines whether the wearabledevice 100 leaves the skin surface according to the detecting results inthe same way as the skin sensor 110 determines whether the wearabledevice 100 leaves the skin surface in the previous embodiments. When thewearable device 100 leaves the skin surface and then approaches the skinsurface between steps 302 and 308, the processor 130 ignores theapproaching of the wearable device 100 to the skin surface after theleaving from the skin surface. In other words, the processor 130 stillconsiders the wearable device 100 as away from the skin surface and thewearable device 100 will be determined to leave the skin surface at step308.

When the skin sensor 110 or the processor 130 determines that thewearable device 100 leaves the skin surface at step 308, that means thewearable device 100 is taken off from the user and the situation is nolonger secure to execute the predetermined function. In response, theflow returns to step 302. When the skin sensor 110 or the processor 130determines that the wearable device 100 does not leave the skin surfaceat step 308, that means the user still wears the wearable device 100 andthe situation is secure to execute the predetermined function. The flowproceeds to step 310.

At step 310, the processor 130 checks whether a request for executing apredetermined function of the wearable device 100 is generated. Therequest can be generated by an external electronic device, such as anNFC terminal for mobile payment, and the wearable device 100 can receivethe request through the wireless communication device 160.Alternatively, the request can be generated by the user through acommand or an operation on the wearable device 100. When the request isnot generated, the flow returns to step 308. When the request isgenerated, the processor 130 receives the request in step 310, and thenthe processor 130 executes the predetermined function in response to therequest at step 312. The processor 130 rejects or ignores the requestwhen the skin sensor 110 or the processor 130 determines that thewearable device 100 leaves the skin surface after the authenticationdata is received and before the predetermined function is executed.

For example, the predetermined function is mobile payment. The requestis generated by an NFC terminal participating in the mobile payment.When the wearable device 100 approaches the NFC terminal, the wearabledevice 100 receives the request. In response to the request, thewearable device 100 cooperates with the NFC terminal to execute themobile payment.

In an embodiment, the skin sensor 110 or the processor 130 determineswhether the wearable device 100 leaves the skin surface at a fixeddetection period (at a fixed detection frequency) during steps 304 to312. In another embodiment, in addition to the determination at thefixed detection period, there is an additional determination of whetherthe wearable device 100 leaves the skin surface performed within thefixed detection period right before the execution of the predeterminedfunction at step 312. This additional determination can be insertedbetween steps 310 and 312 in FIG. 3 . When the wearable device 100leaves the skin surface at any moment between steps 302 and 312, theflow returns to step 302 without executing the predetermined function.

In an embodiment, during the executing of the predetermined function atstep 312, the processor 130 continuously checks whether the wearabledevice 100 leaves the skin surface of the user. As mentioned above, theskin sensor 110 or the processor 130 can determine whether the wearabledevice 100 leaves the skin surface according to the detecting results ofthe sub-sensors in the skin sensor 110. When it is the skin sensor 110that determines whether the wearable device 100 leaves the skin surface,the skin sensor 110 notifies the processor 130 when the wearable device100 leaves the skin surface. Therefore, the processor 130 can respondquickly to the leaving from the skin surface. When the skin sensor 110or the processor 130 determines that the wearable device 100 leaves theskin surface during the executing of the predetermined function at step312, the processor 130 aborts the predetermined function at step 314 byinterrupting the execution of the predetermined function immediatelyregardless of the state and the progress of the execution of thepredetermined function. After step 314, the flow returns to step 302.

The flow of the method in FIG. 3 ensures that the processor 130 executesthe predetermined function if and only if the user wears the wearabledevice 100 initially and then passes the authentication successfully,and the user must keep wearing the wearable device 100 until theprocessor 130 finishes executing the predetermined function. Theprocessor 130 does not execute the predetermined function when thewearable device 100 leaves the skin surface of the user before theprocessor 130 receives the request at step 310. The processor 130 abortsthe predetermined function when the wearable device 100 leaves the skinsurface of the user during the executing of the predetermined functionat step 312.

Therefore, the processor 130 executes the predetermined function only ina secure state wherein the user successfully passes the authenticationand the user keeps wearing the wearable device 100. The sub-sensors inthe skin sensor 110 can detect whether the wearable device 100 leavesthe skin surface at a high frequency (for example, in a range from 1 KHzto 10 KHz) so that the processor 130 can reject the request or abort thepredetermined function immediately after the wearable device 100 istaken off from the authenticated user and an unauthenticated user cannotcontinue the execution of the predetermined function under the identityof the authenticated user.

In an embodiment, the output device 150 includes a display configured todisplay user interfaces. The output device 150 displays a first userinterface when steps 304 and 306 corresponding to the userauthentication are executed and displays a second user interface whenstep 312 corresponding to the predetermined function is executed. Atstep 314, the processor 130 aborts the predetermined function byinterrupting the execution of the predetermined function immediately andswitching the output device 150 from displaying the second userinterface to displaying the first user interface or another differentuser interface. In other words, the predetermined function becomesinaccessible and all information displayed by the predetermined functiondisappears from the display of the output device 150 after the wearabledevice 100 is taken off from the authenticated user. In this way, thewearable device 100 can reliably protect the predetermined function andthe information associated with the predetermined function from beingused or viewed by an unauthenticated user.

For example, the predetermined function is mobile payment. The userpasses the authentication, and then the user generates the request forthe mobile payment through a command or an operation on the wearabledevice 100, and then the output device 150 displays a user interface forthe mobile payment at step 312. The user interface displays a quickresponse code (QR code) representing the user so that a seller can scanthe QR code to receive the payment from the user. When the wearabledevice 100 is taken off from the authenticated user before the sellerscans the QR code, at step 314 the processor 130 aborts the mobilepayment by interrupting the mobile payment immediately and switching theoutput device 150 to display another interface so that anunauthenticated user cannot continue the payment and cannot see or scanthe QR code of the authenticated user.

For another example, the predetermined function is accessing restricteddata, such as reading a message, an email, or an important document ofthe owner of the wearable device 100. The user passes theauthentication, and then the user generates the request for accessingrestricted data through a command or an operation on the wearable device100, and then the output device 150 displays a user interface fordisplaying the message, the email, or the document at step 312. When thewearable device 100 is taken off from the authenticated user, at step314 the processor 130 aborts the data access by immediately switchingthe output device 150 to display another interface so that anunauthenticated user cannot see the restricted data.

For another example, the predetermined function is performing restrictedelectronic transmission, such as performing a data access transactionwith an external database. The user passes the authentication, and thenthe user generates the request for the data access transaction through acommand or an operation on the wearable device 100, and then the outputdevice 150 displays a user interface for accessing the data in theexternal database at step 312. When the wearable device 100 is taken offfrom the authenticated user, at step 314 the processor 130 aborts thedata access transaction by rolling back the data access transaction andterminating the electronic connection between the wearable device 100and the external database. The rolling back means restoring all datamodified in the data access transaction to their original values beforethe data access transaction. In addition, the processor 130 switches theoutput device 150 to display another interface so that anunauthenticated user cannot see the data in the external database.

In an alternative embodiment, the term “the wearing state of thewearable device 100 is adjacent to the skin surface of the user” can bereplaced by the term “the wearable device 100 is adjacent to the skinsurface of the user”, and the term “the wearing state of the wearabledevice 100 is not adjacent to the skin surface of the user” can bereplaced by the term “the wearable device 100 is not adjacent to theskin surface of the user”.

As mentioned above, the skin sensor 110, the PPG sensor 240 or theprocessor 130 can determine whether the wearing state of the wearabledevice 100 is adjacent to the skin surface of the user according to thedetecting results output by the stand-alone PPG sensor 240 or thesub-sensors in the skin sensor 110. The term “adjacent to” means thewearable device 100 is within a preset distance, such as one millimeteror two millimeters, from the skin surface. In another embodiment, thepreset distance can be zero, which means the skin sensor 110, the PPGsensor 240 or the processor 130 is configured to determine whether thewearable device 100 is attached to or in contact with the skin surfaceof the user. Therefore, the term “adjacent to” in the previousembodiments can be replaced with the term “attached to” or the term “incontact with”, and the term “not adjacent to” in the previousembodiments can be replaced with the term “not attached to”, the term“not in contact with” or the term “leave”.

In brief, the wearable device detects an attached status with a user todetermine whether the wearable device is properly worn by a user toimprove confidence of the detected result. Many technologies can beapplied to perform this function. Such as by using a pressure sensor todetect the tension of a belt for fixing the wearable device on theuser's body, or to detect the pressure on the user's skin when thewearable device is wear tightly. Or, by using a capacitive sensor todetect the proximity between the wearable device and the user's skin,the attached status is confirmable. Or, by using a humidity sensor todetect the slight sweat between the wearable device and user's skin, theattached status is confirmable. Or, by using a thermal sensor to detectthe temperature change between the wearable device and user's skin, theattached status is confirmable.

In order to determine whether the attached status is good or not, aprocessor of the wearable device, e.g., a digital processing unit (DSP)or an application specific integrated circuit (ASIC), compares thedetected result (e.g., including pressure, capacitance change, humidityor temperature) of the above sensors with a predetermined threshold,which is previously determined corresponding to a type of sensor. When avariation of the detected result exceeds the predetermined threshold,the attached status is determined to have a change between an attachedstate and a lift up state.

In other aspects, the wearable device confirms the attached status byanalyzing intensity of light passing through different polarizers anddetected by a detection module, by analyzing intensity of differentlight wavelengths detected by the detection module, by analyzingintensity distribution of an image frame detected by the detectionmodule, and by calculating a time-of-flight according to signals (e.g.,avalanche current) detected by a single photon avalanche photodiode(SPAD).

When the user removes the wearable device from his/her body, thewearable device can then detect the status change, and stops generatinga confirmed signal if a lift up state is confirmed. The confirmed signalis to indicate a correct user ID being authenticated.

In the above embodiments, the wearable device is arranged to identify auser ID according to the biometric characteristic of the user. In analternatively embodiment, the wearable device is arranged to identifythe user ID according to a user input which includes a password, agesture, knocks and/or a speech sentence. That is, the biometriccharacteristic being detected by the wearable device is replaced by theuser input.

In an aspect that uses the password as a user input, the wearable deviceincludes a keyboard or a touch panel to receive a set of passwordinputted by a current user. The wearable device then compares theinputted password with a set of pre-stored password to confirm the userID of the current user. The pre-stored password is preferably set orselected by the same user in a setting procedure and stored in a memoryof the wearable device.

In an aspect that uses the gesture as a user input, the wearable deviceincludes a touch panel or an optical gesture detector to detect agesture inputted by a current user, e.g., using his or her finger(s).For the touch panel, the current user draws the gesture on the touchpanel; whereas for the optical gesture detector, the user draws thegesture (e.g., moving finger) in the space in front of the opticalgesture detector. The wearable device then compares the inputted gesturewith a pre-stored gesture to confirm the user ID of the current user.The pre-stored gesture is preferably set or performed by the same userin a setting procedure and stored in a memory of the wearable device.

In an aspect that uses the knocks as a user input, the wearable deviceincludes a gyro or a 2D or 3D acceleration sensor to detect knockingsignals inputted by a current user. The wearable device then comparesthe inputted knocking signals with pre-stored knocking signals toconfirm the user ID of the current user. The pre-stored knocking signalshave a predetermined pattern. As long as the inputted knocking signalshave a same pattern with the predetermined pattern, the wearable deviceconfirms the user ID. The pre-stored knocking signals (or predeterminedpattern) is preferably inputted or performed by the same user in asetting procedure and stored in a memory of the wearable device.

In an aspect that uses the speech sentence as a user input, the wearabledevice includes a microphone to receive a speech sentence said by acurrent user. The wearable device then compares the said speech sentence(including numbers and/or words) with a pre-stored speech sentence toconfirm the user ID of the current user. The pre-stored speech sentenceis preferably inputted or recorded by the same user in a settingprocedure and stored in a memory of the wearable device. That is, thewearable device has the language processing function to process thespeech sentence inputted via the microphone and identifies whether theinputted speech sentence matches a predetermined speech sentence, likean audio password, to identify the user ID.

In another embodiment, the continuously detected heartbeat is expandedto include continuously detected attached status. The attached status isdetected by detecting at least one of a heartbeat, capacitance using acapacitive sensor, light intensity using an optical sensor, atemperature using a thermal sensor, sweat using a humidity sensor. Morespecifically, the heartbeat being continuously detected is used as oneexample to refer that the wearable accessary is continuously being wornby a user. Other methods for confirming the wearable accessary beingcontinuously worn may be used. The change of the attached status fromcontact to non-contact is detectable by detecting a value change of theabove parameters, including with/without heartbeat, capacitancevariation, light intensity variation, capacitance variation, temperaturevariation, humidity variation or the like. The parameter variation iscompared with a predetermined parameter to confirm the change ofattached status.

The wearable device 100 of the present disclosure is selected to operatein a first mode or a second mode, wherein the first mode and the secondmode are respectively entered in different time intervals. In oneaspect, the processor 130 selects to enter the first mode or the secondmode according to a touch or a slip on a touch panel of the wearabledevice 100. In another aspect, the processor 130 selects to enter thefirst mode or the second mode according to a press on a key of thewearable device 100. In an alternative aspect, the processor 130 selectsto enter the first mode or the second mode according to a rotation of aknob of the wearable device 100.

In the first mode, the processor 130 performs the above contactdetection and predetermined function, including e.g., determiningwhether the wearable device 100 is in contact with a skin surface of auser according to a PPG signal generated by a PPG sensor 240, receivingan authentication data for authenticating the user when the wearabledevice 100 is determined to be in contact with the skin surface,executing a predetermined function for the user in response to a requestwhen the authentication data matches a pre-stored data and the wearabledevice 100 is determined to be still in contact with the skin surface,and rejecting or ignoring the request when the wearable device 100 isdetermined to be no longer in contact with the skin surface after theauthentication data is received and before the predetermined function isexecuted. Details of these steps have been illustrated above, and thusare not repeated herein.

In the second mode, the processor 130 generates an average bloodpressure using the PPG signal generated by the PPG sensor 240 asdescribed below.

One aspect of obtaining the blood pressure and the respiration cycle Pb(as shown in FIG. 5 ) from a PPG signal to accordingly generate theaverage blood pressure is illustrated hereinafter.

Firstly, a PPG signal as shown in FIG. 4 is obtained by a PPG sensor 240of the wearable device 100 according to samples acquired at a samplingfrequency of the PPG sensor 240, wherein the sampling frequency iswithin a range between, e.g., 1 KHZ and 10 KHZ, much higher than theheartbeat. These samples form a curve of a PPG signal 11 in FIG. 4 ,e.g., connecting these samples with line segments to form the continuouscurve. In addition to performing different functions in different modesas mentioned above, in another aspect the processor 130 selects a firstpart of the samples of the PPG signal to perform the contact detectionas described above and selects a second part of the samples of the PPGsignal to generate an average blood pressure as described below. Forexample in one aspect, the processor 130 determines whether the wearabledevice 100 is in contact with a skin surface of a user using an odd (oreven) number of the samples of the PPG signal, but calculates the bloodpressure and the respiration cycle using an even (or odd) number of thesamples of the PPG signal. That is, the processor 103 uses interlacedsamples to respectively perform different functions since the samplingfrequency is set high enough compared to the heartbeat.

It is seen from FIG. 4 that the PPG signal 11 includes a plurality offeature points PS1-PS4, PS1′-PS4′. Next, it is able to obtain at leastone blood pressure, as shown in FIG. 5 , corresponding to each pulseduration Pt by recognizing a time difference between two feature pointsof the PPG signal 11 and using an estimation model (described below).FIG. 5 shows a continuous blood pressure signal formed by connecting aplurality of blood pressures with line segments, wherein the numeral 21is a systolic blood pressure signal and the numeral 22 is a diastolicblood pressure signal.

In one aspect, the wearable device 100 is further able to identify arising part and a falling part of the blood pressure signals 21 and 22.As shown in FIG. 5 , the rising part represents a breathe-in and thefalling part represents a breathe-out. In other aspects, correspondingto different estimation models, it is possible that the rising partrepresents a breathe-out and the falling part represents a breathe-in.After the above information is obtained, it is able to further calculatea respiration rate according to the blood pressure signals 21, 22 and toreal-timely output at least one of the blood pressure signals and therespiration rate. In addition, it is possible to generate a prompt forthe user's reference from a prompting device according to a comparisonof comparing the blood pressure and/or respiration cycle with at leastone threshold.

Therefore, by using the wearable device 100 of the present disclosure,it is able to help a user to understand his/her physiological statesmore and achieve the effect of self-adjustment.

The present disclosure is also able to record user's blood pressures andbreathing states for a long period of time to provide statistical datato the user as a reference for the self-adjustment, and it is possibleto further determine thresholds according to said statistical data.

Please referring to FIGS. 6A and 6B, they are usage states of a wearabledevice 100 according to some embodiments of the present disclosure. Thewearable device 100 analyzes and displays the variation of a user'sblood pressure signal changed with time by detecting a PPG signal of theuser's skin tissues. Accordingly, the wearable device 100 is able to bearranged at any suitable location for detecting the PPG signal, e.g.,setting on the user's wrist (FIG. 6A) or the user's arm (FIG. 6B), butnot limited thereto. In another aspect, the wearable device 100 isselected from, e.g., a bracelet, an armband, a ring, a foot ring, a footbracelet, a cell phone, an earphone, a headphone and a personal digitalassistant (PDA) which contacts at least a part of skin surface of auser. In addition, the wearable device 100 is able to be coupled to amedical device, a home appliance, a vehicle, a security system in awired or wireless manner Preferably, the one connected with the wearabledevice 100 includes a display device to real-timely display a detectionresult of the wearable device 100.

Please referring to FIG. 7 , it is a schematic block diagram of awearable device 100 according to another embodiment of the presentdisclosure. The wearable device 100 includes a light source 243, a lightsensor 245 and a processor 130. As mentioned above, the light source 243and the light sensor 245 form a PPG sensor. In some aspects, thewearable device 100 further includes a display device 705 for displayinga detection result of the wearable device 100. In some aspects, thewearable device 100 further includes a transmission interface 704coupled to an external display device 705 in a wired or wireless mannerto output the detection result of the wearable device 100 to the displaydevice 705 to be real-timely displayed. In other words, the displaydevice 705 may or may not be included in the wearable device 100depending on different applications.

The display device 705 is, for example, a liquid-crystal display (LCD),a plasma display panel (PDP), an organic light-emitting diode (OLED)display or a projector for displaying images as long as it is able todisplay average blood pressures 501 and 502 (described later) as shownin FIG. 8 on a screen.

The light source 243 is, for example, a light emitting diode or a laserdiode, and used to emit light adapted to penetrate and be absorbed byskin tissues. For example, a wavelength of light emitted by the lightsource 243 is about 610 nm or 910 nm, but not limited thereto. The lightsource 243 illuminates a skin surface S to cause light to pass throughskin tissues under the skin surface S. Preferably, the wearable device100 includes a transparent surface to be attached to the skin surface Sin operation and for protecting the light source 243, and the lightsource 243 is arranged at an inner side of the transparent surface. Thetransparent surface is made of transparent materials, e.g., plastic orglass, without particular limitations. In some aspects, the transparentsurface is a surface of a light guide which has the function of guidinglight paths.

In some aspects, when the wearable device 100 is also used to detect theblood oxygenation, the wearable device 100 includes two light sources torespectively emit light of different wavelengths, wherein a method ofdetecting the blood oxygenation may be referred to U.S. application Ser.No. 13/614,999 assigned to the same assignee of the present application,and the full disclosure of which is incorporated herein by reference.

The light sensor 245 is, for example, a photodiode or an image sensorarray, e.g., a CMOS sensor array, and used to detect ejected light fromthe skin tissues to generate a PPG signal, shown as 11 in FIG. 4 forexample. The method of detecting and outputting a PPG signal by aphotodiode is known to the art and thus details thereof are notdescribed herein. The present disclosure is to identify the bloodpressure and the respiration rate according to the detected PPG signal.A method of detecting a three dimensional physiology distribution by animage sensor array may be referred to U.S. application Ser. No.14/955,463 assigned to the same assignee of the present application, andthe full disclosure of which is incorporated herein by reference. Eachpixel of the image sensor array respectively outputs the PPG signalmentioned herein, or an intensity summation of all pixels of the imagesensor array is used as the PPG signal mentioned herein. Similarly, thelight sensor 245 is arranged inside of the transparent surface.

The processor 130 is electrically coupled to the light source 243 andthe light sensor 245 to control the light source 243 and the lightsensor 245 to operate correspondingly. The processor 130 calculates ablood pressure corresponding to each pulse duration Pt according to atleast one blood pressure estimation model as well as a time differencebetween two feature points in one pulse duration Pt of the PPG signal11, calculates a respiration cycle Pb, and averages a plurality of bloodpressures within the respiration cycle Pb to generate an average bloodpressure. In one aspect, the average blood pressure is a relative valuewith respect to a real blood pressure of a user. The user is able tounderstand his/her blood pressure change according to the average bloodpressure.

In one aspect, the at least one blood pressure estimation model includesa polynomial taking the time difference between two feature pointswithin one pulse duration Pt as a variable, wherein the polynomial is alinear polynomial, a quadratic polynomial or a higher order polynomialobtained by fitting a curve between the two feature points within thepulse duration Pt by a fitting method. The blood pressure estimationmodel is implemented by software and/or hardware, and integrated in theprocessor 130.

For example in FIG. 4 , a plurality of feature points PS1-PS4 areincluded within one pulse duration Pt, and said two feature points areselected from two of a maximum value PS2, a second maximum value PS4, aminimum value PS1 and a second minimum value PS3 within the pulseduration Pt of the PPG signal 11. In addition, the at least one bloodpressure estimation model includes an estimation model for systolicpressure (SBP) and an estimation model for diastolic pressure (DBP).

The fitting method is used to fit the curve, for example, between thefeature points PS1 and PS2, between the feature points PS2 and PS3,between the feature points PS3 and PS4, between the feature points PS2and PS1′ or between the feature points PS2 and PS4 without particularlimitations.

For example, one estimation model for systolic pressure is an equation(1) obtained according to the curve between the two feature points PS2and PS1′ (PS1′ being the minimum value within a next pulse duration Pt),wherein a time difference between the feature points PS2 and PS1′ isindicated as DT.SBP=−0.095×DT+188.581  (1)

One estimation model for diastolic pressure is an equation (2) obtainedaccording to the curve between the two feature points PS2 and PS4,wherein a time difference between the feature points PS2 and PS4 isindicated as T1. To clearly show the time difference, T1 is shown by atime difference between the feature points PS2′ and PS4′ in FIG. 4 ,i.e., assuming time differences between feature points PS2′ and PS4′ andbetween feature points PS2 and PS4 being identical.DBP=−0.344×T1+174.308  (2)

The above diastolic blood pressure model and systolic blood pressuremodel are only intended to illustrate and able to obtain rough values ofthe blood pressure corresponding to the measured PPG signal. If a moreprecise model is required, it is possible to use other mathematicalmodels without particular limitations, e.g., using a higher orderpolynomial having more variables or more different time differences.

For example, it is possible to represent the SBP and DPP by an equationΣakXkK+C, wherein Xk indicates a time difference and C is a knownconstant.

One estimation model for systolic pressure and one estimation model fordiastolic pressure are obtainable between arbitrary two feature points,and only values of the estimated blood pressure are different. In thisaspect, the estimation model for systolic pressure and the estimationmodel for diastolic pressure are preferably a common model obtained bygathering statistics of PPG signals of some people before shipment andstored in a nonvolatile memory of the processor 130. It should bementioned that said feature points are not limited to those given in thepresent disclosure but determined by positions in the PPG signal thatcorrespond to maximum/minimum values in a linear differential curve or aquadratic differential curve of the PPG signal. In addition, a number offeature points for determining the blood pressure estimation model isnot limited to 2.

The processor 130 obtains one systolic blood pressure respectivelycorresponding to each pulse duration Pt, for example, using the equation(1) to form a systolic blood pressure signal 21 as shown in FIG. 5 ,wherein each dot in the systolic blood pressure signal 21 is onesystolic blood pressure obtained by the equation (1), and these dots areconnected by line segments. The processor 130 obtains one diastolicblood pressure respectively corresponding to each pulse duration Pt, forexample, using the equation (2) to form a diastolic blood pressuresignal 22 as shown in FIG. 5 , wherein each dot in the diastolic bloodpressure signal 22 is one diastolic blood pressure obtained by theequation (2), and these dots are also connected by line segments.

In this aspect, the processor 130 further calculates a respiration cyclePb according to the systolic blood pressure signal 21 and/or thediastolic blood pressure signal 22. In one aspect, the processor 130uses a fast Fourier transform (FFT) to convert a plurality of bloodpressures of the systolic blood pressure signal 21 and/or the diastolicblood pressure signal 22 to a frequency domain and then obtains therespiration cycle Pb. In another aspect, the processor 130 calculatesthe respiration cycle Pb using a time difference between two adjacentpeak blood pressures among a plurality of blood pressures of thesystolic blood pressure signal 21 and/or the diastolic blood pressuresignal 22. In other words, it is possible to take a period of thesystolic blood pressure signal 21 and/or the diastolic blood pressuresignal 22 as the respiration cycle Pb.

It is seen from FIG. 5 that the systolic blood pressure signal 21 andthe diastolic blood pressure signal 22 obtained by the processor 130change with the breathing of a user and are unstable in amplitude.Accordingly, the processor 130 further calculates an average value(e.g., the root-mean-square, but not limited to) of a plurality of bloodpressures within the respiration cycle Pb so as to obtain the averageblood pressure as shown in FIG. 8 , wherein the numeral 501 is referredto the systolic blood pressure and the numeral 502 is referred to thediastolic blood pressure. FIG. 8 is obtained by setting the respirationcycle Pb as 6 seconds. The interval of the respiration cycle Pb isdifferent according to different scenarios. It can been seen from FIG. 8that the average blood pressure shown in FIG. 8 is much more stable thanthe blood pressure in FIG. 5 .

Referring to FIG. 8 again, it further shows a plurality of measuredblood pressures measured by a hemadynamometer. As mentioned above, thewearable device 100 of the present disclosure measures relative bloodpressures. In some embodiments, the memory further stores at least onecalibration value, wherein the calibration value is a difference valuebetween a measured blood pressure by a hemadynamometer and an estimatedblood pressure calculated by the blood pressure estimation model of thepresent disclosure. Accordingly, after the processor 130 obtains theestimated blood pressure (e.g., the average blood pressure 501 and 502),the calibration value is added to or subtracted from the estimated bloodpressure for calibration thereby obtaining a more accurateindividualized blood pressure, i.e. calibration values are measured andstored corresponding to different users respectively so as to obtainindividualized calibration values.

The transmission interface 704 outputs at least one of the average bloodpressure and a respiration rate in a wired or wireless manner, e.g.,outputting data of at least one of the average blood pressure and arespiration rate at a predetermined frequency to a display device 705for real-time display, wherein said wired and wireless transmissiontechniques are known to the art and thus details thereof are notdescribed herein. The respiration rate is obtainable according to therespiration cycle Pb, e.g., a reciprocal of the respiration cycle Pbmultiplied by 60 seconds. It is appreciated that when the wearabledevice 100 also includes the display device 705, the transmissioninterface 704 is not implemented, or the transmission interface 704 isarranged inside the wearable device 100 between the processor 130 andthe display device 705.

The display device 705 real-timely displays a variation curve of theaverage blood pressure (e.g., the estimated blood pressures 501 and 502shown in FIG. 8 ) changed with time and/or values of the respirationrate. In addition, the processor 130 further reads at least one bloodpressure threshold TH_(S), TH_(D) associated with the blood pressurefrom the memory, and sends the read values to the display device 705directly or via the transmission interface 704 to be displayed thereon.For example, lines, numbers or graphics are shown on a screen of thedisplay device 705 to mark the blood pressure thresholds TH_(S), TH_(D)and values of the respiration rate to allow a user to easily observehis/her blood pressures and breathing states from the display device705.

Different from conventional blood pressure detection devices, thewearable device 100 of the present disclosure is able to real-timelydisplay the blood pressure and breathing state of a user. In otherwords, as the wearable device 100 analyzes a PPG signal detected by thePPG sensor 240, when the processor 130 receives the PPG signal, theprocessor 130 starts to analyze and output the blood pressure signals 21and 22 and/or the respiration rate to the display device 705 to bedisplayed thereon. As the processor 130 averages the blood pressuresignals 21 and 22 by the respiration cycle Pb, the display device 705 isable to display blood pressures after one respiration cycle Pb.Generally, under normal condition, the respiration cycle Pb is about 5to 6 seconds. It is appreciated that different users have differentrespiration cycles Pb, and different scenarios have differentrespiration cycles Pb. In other aspects, when the processor 130 does notcalculate the average blood pressure, the display device 705 real-timelydisplays, for example, blood pressure signals 21 and 22 as shown in FIG.5 .

In addition, to improve the user experience, the wearable device 100further includes a prompt device to output a prompt signal according toa comparison of comparing at least one threshold with the average bloodpressure and/or respiration cycle, wherein the prompt signal is, e.g., avibration signal, a light signal, an audio signal and/or an image signalwithout particular limitations as long as the user can be informed.

The wearable device 100 of the present disclosure is applicable toadjusting the emotion as well as the work and rest.

For example, when a user's average blood pressure does not reach orexceeds the blood pressure thresholds TH_(S) and TH_(D), the promptdevice outputs a prompt signal. Accordingly, the user changes emotion,takes medicine, puts on or takes off clothes and so on to cause theaverage pressure to return to a normal status.

For example, when a user's respiration rate does not reach or exceeds athreshold, the prompt device outputs a prompt signal. A frequency valueof the respiration rate and the estimated blood pressures 501 and 502are shown together on a screen. As mentioned above, the processor 130 isable to obtain the respiration rate within one respiration cycle Pbwithout accumulating count values for a whole minute.

The indicating method of the prompt signal is determined according todifferent applications.

For example, the display device 705 may also be used as the promptdevice. When the average blood pressure and/or the respiration rateexceed or do not reach the threshold, the processor 130 provides imagesignals to the display device 705 to make the display device 705 displaythe prompt, e.g., by words, graphs, brightness and so forth.

For example, the wearable device 100 further includes a vibrator 706 asthe prompt device. When the average blood pressure and/or therespiration rate exceed or do not reach the threshold, the processor 130provides vibration signals to the vibrator 706 to make the vibrator 706generate vibrations to warn the user.

For example, the wearable device 100 further includes a speaker 707 asthe prompt device. When the average blood pressure and/or therespiration rate exceed or do not reach the threshold, the processor 130provides voice signals to the speaker 707 to make the speaker 707generate sounds to warn the user.

For example, the wearable device 100 further includes a warning lightsource 708 used as the prompt device. When the average blood pressureand/or the respiration rate exceed or do not reach the threshold, theprocessor 130 provides optical signals to the warning light source 708to make the warning light source 708 illuminate light to warn the user.

In some aspects, the processor 130 is built-in, for example, a learningalgorithm (e.g., implemented by software and/or hardware), to determinethe above thresholds, e.g., blood pressure threshold and the respirationrate threshold, but not limited thereto, according to the user'shistorical records. For example, the thresholds are divided into sleeptime, work time, sports time and so forth. Information related to thehistorical records is stored in, for example, a non-volatile memory.

Please referring to FIG. 9 , it is a flow chart of an operating methodof a wearable device 100 according to one embodiment of the presentdisclosure, which includes the steps of: obtaining, by a light sensor, aPPG signal from a skin surface (step S61); calculating, by a processor,a blood pressure corresponding to each pulse duration according to atleast one blood pressure estimation model and a time difference betweentwo feature points within one pulse duration of the PPG signal (stepS62); calculating, by the processor, a respiration cycle (step S63), andaveraging, by the processor, a plurality of blood pressures within therespiration cycle to generate an average blood pressure (step S64).

Step S61: The wearable device 100 is preferably fixed with respect to askin surface S in operation such that a PPG signal detected by the lightsensor 245 of the PPG sensor 240 is not affected by noises due tomovement. In addition, the processor 130 is further built-in with analgorithm for eliminating the noises in PPG signals caused by themovement, wherein a method of eliminating motion noises may be referredto U.S. application Ser. No. 13/614,999 assigned to the same assignee ofthe present application, and the full disclosure of which isincorporated herein by reference.

Step S62: The processor 130 starts to identify feature points within onepulse duration Pt (e.g., PS1-PS4 in FIG. 4 ) of a PPG signal right afterreceiving the PPG signal from the light sensor 245 of the PPG sensor240, wherein said identifying is implemented by software and/orhardware. At least one blood pressure estimation model is pre-stored ina memory, wherein the at least one blood pressure estimation modelincludes a polynomial using a time difference between two feature pointswithin one pulse duration Pt as a variable, e.g., equations (1) and (2).The processor 130 puts the time differences (e.g., ST, DT, T1) betweenthe measured feature points PS1-PS4 into the at least one blood pressureestimation model to calculate a blood pressure corresponding to eachpulse duration Pt, as shown in FIG. 5 .

Steps S63-S64: After obtaining a plurality of blood pressures, theprocessor 130 calculates a respiration cycle Pb (as shown in FIG. 5 )directly in the time-domain or calculates the respiration cycle Pb inthe frequency domain by using the fast Fourier transform (FFT). In thisaspect, the respiration cycle Pb is for calculating a respiration rateto be displayed by the display device 705 and for averaging a pluralityof blood pressures calculated by the processor 130 to obtain theestimated blood pressures 501 and 502 as shown in FIG. 8 .

Next, the respiration rate and/or the estimated blood pressures 501 and502 are sent to a display device 705 to be real-timely displayedthereon. In addition, the processor 130 further compares the respirationrate and/or the estimated blood pressures 501, 502 with at least onethreshold to confirm whether values thereof are within a normal range toaccordingly generate a prompt signal.

In some aspects, to obtain personalized blood pressures, a differencevalue between an estimated blood pressure and a measured blood pressureof a hemadynamometer is stored in a memory to be used as a calibrationvalue, wherein the calibration value is stored by an application (APP)in a calibration stage, e.g., a user inputting the difference valuebetween the estimated blood pressures and measured blood pressures inFIG. 8 into a user interface to be stored. During operation, theprocessor 130 automatically calibrates the estimated blood pressures 501and 502 with the stored calibration value.

It should be mentioned that, it is possible that the display device 705displays the estimated blood pressures 501, 502 and the respiration ratebut does not display the measured blood pressures. In some aspects, thedisplay device 705 further displays the systolic blood pressure signal21 and/or the diastolic blood pressure signal 22 depending onapplications thereof.

It should be mentioned that although the above aspects take thereflective optical PPG sensor as an example, it is only intended toillustrate but not to limit the present disclosure. In other aspects,the PPG sensor is a transmissive optical device in which disposedpositions of the light source and the light sensor are different fromthe above aspects but the sensing theory is not changed, and thusdetails thereof are not repeated herein.

It should be mentioned that in the above aspects a memory disposed inthe processor 130 is taken as an example for illustration purposes, butthe present disclosure is not limited thereto. In other aspects, thememory 130 is located outside of the processor 130 without particularlimitations as long as the processor 130 is able to access the memory.

In addition, in some aspects, when the processor 130 identifies that thevariation of obtained blood pressures (e.g., the standard deviation)exceeds a predetermined range, the calculation of the average bloodpressure or the outputting of estimated blood pressures being obtainedis stopped till the obtained blood pressures return to the predeterminedrange.

Although the disclosure has been explained in relation to its preferredembodiment, it is not used to limit the disclosure. It is to beunderstood that many other possible modifications and variations can bemade by those skilled in the art without departing from the spirit andscope of the disclosure as hereinafter claimed.

What is claimed is:
 1. A wearable device, comprising: aphotoplethysmography (PPG) sensor configured to generate a PPG signal;and a processor, configured to receive an authentication data forauthenticating a user when the wearable device is determined to be incontact with a skin surface of the user according to the PPG signal,execute a predetermined function for the user in response to a requestwhen the authentication data matches a pre-stored data and the wearabledevice is determined to be still in contact with the skin surfaceaccording to the PPG signal, and reject or ignore the request when thewearable device is determined to be no longer in contact with the skinsurface according to the PPG signal after the authentication data isreceived and before the predetermined function is executed, wherein theprocessor is further configured to calculate at least one blood pressurecorresponding to each pulse duration according to at least one bloodpressure estimation model and a time difference between two featurepoints within one pulse duration of the PPG signal, and averagecalculated blood pressures within a predetermined time interval togenerate an average blood pressure.
 2. The wearable device of claim 1,wherein the at least one blood pressure estimation model comprises apolynomial using the time difference between the two feature pointswithin the one pulse duration as a variable.
 3. The wearable device ofclaim 1, wherein the two feature points are two of a maximum value, asecond maximum value, a minimum value and a second minimum value withinthe pulse duration of the PPG signal.
 4. The wearable device of claim 1,wherein the processor is further configured to calculate a respirationcycle according to a plurality of blood pressures using a fast Fouriertransform.
 5. The wearable device of claim 1, wherein the processor isfurther configured to calculate a respiration cycle using a timedifference between two adjacent minimum blood pressures among aplurality of blood pressures.
 6. The wearable device of claim 1, whereinthe at least one blood pressure estimation model comprises an estimationmodel for systolic pressure and an estimation model for diastolicpressure.
 7. The wearable device of claim 1, wherein the predeterminedfunction comprises mobile payment, accessing restricted data, andperforming restricted electronic transmission.
 8. A wearable device,comprising: a photoplethysmography (PPG) sensor configured to generate aPPG signal; and a processor, configured to enter a first mode or asecond mode, wherein in the first mode, the processor is configured toreceive an authentication data for authenticating a user when thewearable device is determined to be in contact with a skin surface ofthe user according to the PPG signal, execute a predetermined functionfor the user in response to a request when the authentication datamatches a pre-stored data and the wearable device is determined to bestill in contact with the skin surface according to the PPG signal, andreject or ignore the request when the wearable device is determined tobe no longer in contact with the skin surface according to the PPGsignal after the authentication data is received and before thepredetermined function is executed, and in the second mode, theprocessor is configured to calculate at least one blood pressurecorresponding to each pulse duration according to at least one bloodpressure estimation model and a time difference between two featurepoints within one pulse duration of the PPG signal, and averagecalculated blood pressures within a predetermined time interval togenerate an average blood pressure.
 9. The wearable device of claim 8,wherein the at least one blood pressure estimation model comprises apolynomial using the time difference between the two feature pointswithin the one pulse duration as a variable.
 10. The wearable device ofclaim 8, wherein the two feature points are two of a maximum value, asecond maximum value, a minimum value and a second minimum value withinthe pulse duration of the PPG signal.
 11. The wearable device of claim8, wherein the processor is further configured to calculate arespiration cycle according to a plurality of blood pressures using afast Fourier transform.
 12. The wearable device of claim 8, wherein theprocessor is further configured to calculate a respiration cycle using atime difference between two adjacent minimum blood pressures among aplurality of blood pressures.
 13. The wearable device of claim 8,wherein the at least one blood pressure estimation model comprises anestimation model for systolic pressure and an estimation model fordiastolic pressure.
 14. The wearable device of claim 8, wherein theprocessor is configured to enter the first mode or the second modeaccording to a touch or a slip on a touch panel of the wearable device,according to a press on a key of the wearable device, or according to arotation of a knob of the wearable device.
 15. A wearable device,comprising: a photoplethysmography (PPG) sensor configured to generate aPPG signal according to samples acquired at a sampling frequency of thePPG sensor; and a processor, configured to receive an authenticationdata for authenticating a user when the wearable device is determined tobe in contact with a skin surface of the user according to an odd numberof the samples of the PPG signal, execute a predetermined function forthe user in response to a request when the authentication data matches apre-stored data and the wearable device is determined to be still incontact with the skin surface according to the odd number of the samplesof the PPG signal, and reject or ignore the request when the wearabledevice is determined to be no longer in contact with the skin surfaceaccording to the odd number of the samples of the PPG signal after theauthentication data is received and before the predetermined function isexecuted, wherein the processor is further configured to calculate atleast one blood pressure corresponding to each pulse duration accordingto at least one blood pressure estimation model and a time differencebetween two feature points within one pulse duration of the PPG signalusing an even number of the samples of the PPG signal, and averagecalculated blood pressures within a predetermined time interval togenerate an average blood pressure.
 16. The wearable device of claim 15,wherein the at least one blood pressure estimation model comprises apolynomial using the time difference between the two feature pointswithin the one pulse duration as a variable.
 17. The wearable device ofclaim 15, wherein the two feature points are two of a maximum value, asecond maximum value, a minimum value and a second minimum value withinthe pulse duration of the PPG signal.
 18. The wearable device of claim15, wherein the processor is further configured to calculate arespiration cycle according to a plurality of blood pressures using afast Fourier transform.
 19. The wearable device of claim 15, wherein theprocessor is further configured to calculate a respiration cycle using atime difference between two adjacent minimum blood pressures among aplurality of blood pressures.
 20. The wearable device of claim 15,wherein the at least one blood pressure estimation model comprises anestimation model for systolic pressure and an estimation model fordiastolic pressure.